Given the dominance of the free to play model and in-app purchases offered in the gaming industry, games have become more of a service than a product. With this change, in-game analytics is critical to constantly engage and monetize users to stay competitive. AWS offers a comprehensive suite of analytics solutions to help you keep your players engaged and optimize your game to increase revenue. Watch a short video to learn how AWS can help you with building a scalable analytics pipeline.

The world of gaming never sleeps, neither does the player data generation. Game engines send these data to EC2 instances that are auto-scaled and create telemetry. Ingest data with Kinesis and store data with S3 for future analysis. You can leverage EMR and Redshift for batch processing for workloads that are not time sensitive, or Elasticsearch for real time analytics to monitor player activities and revenue trend. Finally, use Amazon Quicksight to visualize data to make strategic decisions to optimize your game.

Amazon Kinesis enables you to take in large quantities of data (hundreds of terabytes per hour) and take action on it in real-time. You can look at player experiences, advertising effectiveness, and game usage statistics in real-time to improve your user’s experience.

Amazon EMR to track player performance and make data informed decisions to optimize your games. With connectors available for Amazon S3, Kinesis, DynamoDB and more, use your favorite tool of choice in the Hadoop Ecosystem to process data.

Use Amazon Redshift to use familiar SQL like tools to gain deeper understanding of how players are engaging your games leveraging massive amounts of data for the fraction of the cost of a traditional data warehouse.

To analyze player data stored in Amazon S3, use Amazon Athena. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds.

Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. Its flexible data model, reliable performance, and automatic scaling of throughput capacity, makes it a great fit for gaming workloads.

Connecting with Your Customers - Building Successful Mobile Games through the Power of AWS Analytics

Learn how to leverage new features of AWS services such as Elastic MapReduce, Amazon S3, Kinesis, and Redshift to build an end-to-end analytics pipeline. Plus, we’ll show you how to easily integrate analytics with other AWS services in your game.

Glu uses Amazon Kinesis, Apache Storm, S3, and Hadoop to collect billions of data points from millions of user devices in real-time every single day. This session describes how Glu built and configured an array of producers to submit real-time gaming events into Amazon Kinesis, using temporary tokens from Amazon Cognito, removing the need for an intermediate store-forward fleet.

Building an Event-Based Analytics Pipeline for Amazon Game Studios’ Breakaway

Learn how Amazon Game Studio built a telemetry pipeline on AWS to ingest, store, and analyze gameplay telemetry to help them answer important game design questions. The elastic scalability and pay-as-you-go cost model of AWS made it the perfect platform to quickly assemble a working analytics pipeline during development and be able to scale that pipeline over time to handle their production workload.